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Looking at 135 Canadian urban areas over a 35-year period (1971-2006), the paper examines the relationship between initial specialisation (using employment) in resource industries and various growth indicators via a mix of descriptive statistics and econometric modelling. The paper differentiates between two resources sectors: resource extraction (mining, logging, etc.); primary resource transformation (paper mills, foundries, smelters, etc.). The evidence for a 'resource curse' is mixed. Resource transformation industries are found to be associated with slower population growth, also depressing growth in college-educated cohorts. However, no such relationship is found for resource extraction. We find no evidence for a durable Dutch Disease wage effect. Wages fluctuate in response to resource demand as do working-age populations. Many relationships hold only for the short run. In the end, we argue, the impact of resource specialisation depends on the particular resource and type of industry it spawns, as well as location. There is no generalisable resource curse, valid for all resources and all places. [ABSTRACT FROM AUTHOR]

Local and regional employment growth is generally studied either by searching for local qualitative explanatory factors such as governance, synergy between firms, and milieu effects, or by searching for general growth factors using statistical techniques. The body of work that relies on this approach has tended, in keeping with economics’ nomothetic tradition, to assume that local and regional growth factors are constant over space. The focus of this paper is on exploring the spatial stationarity of employment growth factors in Canada, but it also seeks to clarify some of the broad principles behind spatial regression techniques in order to provide a point of entry and a conceptual framework for empirical researchers. To do so, we apply a recently developed technique, Geographically Weighted Regression (GWR), and we explore the method's advantages and limits for answering our research question. We find evidence that growth factors differ across Canada, but we also conclude that the GWR technique, given the number and shape of regions available for our analysis and given certain limitations that are currently inherent to the method, can only provide tentative and exploratory results. [ABSTRACT FROM AUTHOR]

Examines number of hypotheses concerning the factors or correlates of employment growth in the Canadian urban system. Attributes of an urban area; Most fundamental characteristic of the analyses conducted.

The determinants of rural and urban community population change over the period 1991–2001 are investigated at a very fine level of disaggregation for Canada. The study examines the influence of local amenities, economic factors, and agglomeration economies on population growth for age cohorts starting from the very young to the elderly. Motivated by the objective of assessing the overall jobs versus people question in economic development, the emphasis is on estimating the relative contribution of groupings of variables in explaining the variations in population change rather than the contribution of individual variables. Results indicate that rural and urban populations are influenced to differing degrees by amenity, economic, and urban scale groupings of variables and that there are variations among age cohorts in both urban and rural areas. While economic variables are the most influential in population change for all rural cohorts, their contribution somewhat diminishes with age. In urban areas, amenity, and economic variable groupings have approximately equal importance across all cohorts. For the key young adult cohort, the economic grouping is clearly the most influential in rural areas, while it is a close second to amenities in urban areas. [ABSTRACT FROM AUTHOR]